Adaptive pixel-to-pixel projection intensity adjustment for measuring a shiny surface using orthogonal color fringe pattern projection

Abstract

Three-dimensional (3D) shape measurement based on fringe pattern projection techniques has been commonly used in various fields. One of the remaining challenges in fringe pattern projection is that camera sensor saturation may occur if there is a large range of reflectivity variation across the surface that causes measurement errors. To overcome this problem, a novel fringe pattern projection method is proposed to avoid image saturation and maintain high-intensity modulation for measuring shiny surfaces by adaptively adjusting the pixel-to-pixel projection intensity according to the surface reflectivity. First, three sets of orthogonal color fringe patterns and a sequence of uniform gray-level patterns with different gray levels are projected onto a measured surface by a projector. The patterns are deformed with respect to the object surface and captured by a camera from a different viewpoint. Subsequently, the optimal projection intensity at each pixel is determined by fusing different gray levels and transforming the camera pixel coordinate system into the projector pixel coordinate system. Finally, the adapted fringe patterns are created and used for 3D shape measurement. Experimental results on a flat checkerboard and shiny objects demonstrate that the proposed method can measure shiny surfaces with high accuracy.

Adaptive Binocular Fringe Dynamic Projection Method for High Dynamic Range Measurement

“…Addressing that it is difficult to improve the dynamic range by hardware for the most camera sensors [6], many experts have carried out a series of approaches to solve the HDR measurement problem. The methods can be divided into several categories: multi-exposure method [12,13,14], light intensity adjustment method [15,16], color invariance method [17,18,19], polarization method [20,21,22], adaptive fringe pattern method [23,24,25,26,27], and others [28,29]. Considering that the dark regions and bright regions of the fringe image require different exposure times, multi-exposure method becomes a way for HDR problem [12,13,14].…”

Hybrid 3D Shape Measurement Using the MEMS Scanning Micromirror

“…Some other researchers have attempted to adjust the parameters of the camera and projector to handle the surface with large reflection variations. Lin et al [21,22] suggest adjusting the maximum input gray level of projecting image globally, while Chen et al [23,24] proposed adjusting projecting images pixel-by-pixel. In [16,25], the author proposes projecting a set of fringe images that are captured with different exposures.…”

“…In [16,25], the author proposes projecting a set of fringe images that are captured with different exposures. For [16,21,22,23,24,25], the reflection of the surface needs to be calibrated first. Then, by fusing these images captured with different parameters, a new fringe pattern with fewer saturated regions can be obtained.…”

“…Then, by fusing these images captured with different parameters, a new fringe pattern with fewer saturated regions can be obtained. Although Jiang et al [16,20,21,22,23,24,25] improve the performance without adding any extra equipment, they need to project or capture a lot of images when the measuring surface has very complex reflection variations. On the other hand, these approaches still use an FPP principle, which can be ineffective for extreme reflection areas.…”

Development of a new dual‐pattern fringe projection scanner

“…As mentioned, some uncertainties are related to an object's material or its geometry. The colour (Zhou et al, 2012), texture (Lin et al, 2017), specularity (Jeong et al, 2007) and change in surface reflectivity (Chen et al, 2018) are those corresponding to the object's material. Je et al (2004) enhanced the colour contrast of the pattern to achieve more distinguishable strips.…”